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87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
import json
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import logging
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logger = logging.getLogger(__name__)
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class ToolActionParser:
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def __init__(self, llm_type, name_mapping=None):
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self.llm_type = llm_type
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self.name_mapping = name_mapping
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self.parsers = {
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"OpenAILLM": self._parse_openai_llm,
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"GoogleLLM": self._parse_google_llm,
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}
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def parse_args(self, call):
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parser = self.parsers.get(self.llm_type, self._parse_openai_llm)
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return parser(call)
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def _resolve_via_mapping(self, call_name):
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"""Look up (tool_id, action_name) from the name mapping if available."""
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if self.name_mapping and call_name in self.name_mapping:
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return self.name_mapping[call_name]
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return None
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def _parse_openai_llm(self, call):
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try:
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call_args = json.loads(call.arguments)
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resolved = self._resolve_via_mapping(call.name)
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if resolved:
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return resolved[0], resolved[1], call_args
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# Fallback: legacy split on "_" for backward compatibility
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tool_parts = call.name.split("_")
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if len(tool_parts) < 2:
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logger.warning(
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f"Invalid tool name format: {call.name}. "
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"Could not resolve via mapping or legacy parsing."
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)
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return None, None, None
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tool_id = tool_parts[-1]
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action_name = "_".join(tool_parts[:-1])
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if not tool_id.isdigit():
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logger.warning(
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f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call."
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)
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except (AttributeError, TypeError, json.JSONDecodeError) as e:
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logger.error(f"Error parsing OpenAI LLM call: {e}")
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return None, None, None
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return tool_id, action_name, call_args
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def _parse_google_llm(self, call):
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try:
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call_args = call.arguments
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resolved = self._resolve_via_mapping(call.name)
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if resolved:
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return resolved[0], resolved[1], call_args
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# Fallback: legacy split on "_" for backward compatibility
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tool_parts = call.name.split("_")
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if len(tool_parts) < 2:
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logger.warning(
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f"Invalid tool name format: {call.name}. "
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"Could not resolve via mapping or legacy parsing."
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)
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return None, None, None
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tool_id = tool_parts[-1]
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action_name = "_".join(tool_parts[:-1])
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if not tool_id.isdigit():
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logger.warning(
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f"Tool ID '{tool_id}' is not numerical. This might be a hallucinated tool call."
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)
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except (AttributeError, TypeError) as e:
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logger.error(f"Error parsing Google LLM call: {e}")
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return None, None, None
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return tool_id, action_name, call_args
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